Top Machine Learning Jobs in Ankara

Develop, design, test and implement imaging and 3D reconstruction algorithms using C++ and Python. Analyze real data, optimize for high-performance computing, integrate algorithms into applications, and collaborate across algorithms, physics, and electronics teams while participating in design and code reviews.

Develop, train, evaluate, and optimize ML solutions and data pipelines; translate business requirements into production-ready ML code; perform feature engineering, model selection, and evaluation; document work, participate in code reviews, and support testing and data issue resolution.

Own and scale APAC programmatic advertising strategy to drive user acquisition, retention, and ROAS. Lead media buying across auctions, PMPs, preferred deals and PG; leverage AI/ML and automation; set best practices for targeting, frequency, remarketing, brand safety and DCO; research and scale emerging channels like CTV, audio, contextual and DOOH.

Build and maintain user tagging and profiling systems, analyze large-scale behavior data, perform feature engineering and exploratory analysis, support cross-functional teams for segmentation, monitor tag effectiveness, detect anomalies and fraud patterns, and improve data methodologies to enable risk control and personalized services.

Lead a Data Analyst team to analyze PB-scale transactional and customer data, build algorithmic systems and visualizations, implement ML/LLM solutions for compliance use cases, support business stakeholders with data requests, and translate findings into actionable recommendations.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Lead design and management of search and content recommendation services and models. Build personalized recommender systems using ML/AI, define success metrics with product and business teams, drive core module development, and translate PB-scale data insights into measurable product impact.

Design, back-test and implement pricing, risk management, and agency trading strategies; collaborate with developers to integrate models into the trading platform; participate in product ideation, modeling, parameter tuning, and risk evaluation.

Design, develop, and manage large-scale search and content recommendation systems. Apply ML-based personalization to improve content matching and distribution. Lead core recommendation module development, define success metrics, and collaborate with content, product, and business teams to drive AI product upgrades and better user and business outcomes.

Design, build, and manage large-scale search and content recommendation systems using machine learning and personalization techniques. Collaborate with content, product, and business teams to define success metrics, drive AI product improvements, and maximize content value and user impact.

Early-career Performance Engineer in the Binance Accelerator Program. Perform hands-on performance testing and tuning, design AI-powered test strategies using LLMs and ML, build AI-driven anomaly detection and bottleneck analysis tools, research new AI technologies, and improve reliability of large-scale distributed systems.

Lead the Recommendations engineering team to build scalable, reliable recommendation-as-a-service products. Own recommendation quality and business impact, set technical direction, translate product goals into engineering plans, ensure SLAs, hire and coach engineers, and drive system reliability and scalability.

Lead product strategy and roadmap for query interpretation and search quality. Own models, tools, and metrics to optimize recall and precision. Collaborate with ML, infra, and product teams, triage quality issues, benchmark competitors, and build evaluation frameworks and explainability for search results.

Design and develop AI-driven features to enhance customer experience, execute ML projects, and optimize AI performance while collaborating cross-functionally.

The Head of Education & Community at Siena is responsible for developing product education, onboarding programs, community events, and market education resources. This role involves creating curricula, conducting workshops, and supporting sales with training and demos while leveraging AI for teaching efficiency.

As a Senior Product Manager at Acronis, you will define product strategy, understand customer needs, lead market analysis, prioritize execution, and collaborate with sales and marketing to ensure successful product launches and ongoing success.

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.

The Head of Computer Vision will lead a team of ML Engineers, drive the long-term ML strategy, focus on breakthrough innovations, and establish cross-functional partnerships while mentoring and scaling the team effectively.

As a Customer Success Manager, you will oversee Turkish accounts, ensuring value realization from digital twin technology, managing relationships, and identifying upselling opportunities.

The Senior Data Scientist will perform data analysis, design AI systems, build data pipelines, and collaborate with cross-functional teams to drive solutions in mobile growth using machine learning and AI.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

The Customer Solutions Manager will lead customer engagement, resolve technical issues, advocate for customer needs, and leverage AI and data analytics for better solutions.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.